

from __future__ import annotations

import math

__snake_case				:      Union[str, Any]   		=			"""2020.9.26"""
__snake_case				:      Union[str, Any]   		=			"""xcodz-dot, cclaus, dhruvmanila"""


def 					_UpperCAmelCase				(						a__  ,	a__  ,	a__  ,	a__  ,	a__):

			'''simple docstring'''



			if not all(isinstance(a__  ,	(float, int)) for val in locals().values()):
						a_						:						Tuple 							= f'''Input values must either be float or int: {list(locals().values())}'''
						raise TypeError(a__)
			a_						:						Dict 							= ((x * distance) / (z + distance)) * scale
			a_						:						Dict 							= ((y * distance) / (z + distance)) * scale
			return projected_x, projected_y


def 					_UpperCAmelCase				(						a__  ,	a__  ,	a__  ,	a__  ,	a__):

			'''simple docstring'''



			if not isinstance(a__  ,	a__):
						raise TypeError("""Axis must be a str""")
			a_						:						List[Any] 							= locals()
			del input_variables["axis"]
			if not all(isinstance(a__  ,	(float, int)) for val in input_variables.values()):
						a_						:						Optional[int] 							= (
						    """Input values except axis must either be float or int: """
						    f'''{list(input_variables.values())}'''
						)
						raise TypeError(a__)
			a_						:						Tuple 							= (angle % 3_6_0) / 4_5_0 * 1_8_0 / math.pi
			if axis == "z":
						a_						:						Union[str, Any] 							= x * math.cos(a__) - y * math.sin(a__)
						a_						:						Dict 							= y * math.cos(a__) + x * math.sin(a__)
						a_						:						Union[str, Any] 							= z
			elif axis == "x":
						a_						:						Dict 							= y * math.cos(a__) - z * math.sin(a__)
						a_						:						Tuple 							= z * math.cos(a__) + y * math.sin(a__)
						a_						:						List[Any] 							= x
			elif axis == "y":
						a_						:						int 							= x * math.cos(a__) - z * math.sin(a__)
						a_						:						Any 							= z * math.cos(a__) + x * math.sin(a__)
						a_						:						Union[str, Any] 							= y
			else:
						raise ValueError("""not a valid axis, choose one of 'x', 'y', 'z'""")

			return new_x, new_y, new_z


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	print(F"""{convert_to_ad(1.0, 2.0, 3.0, 10.0, 10.0) = }""")
	print(F"""{rotate(1.0, 2.0, 3.0, "y", 90.0) = }""")





from random import randint
from tempfile import TemporaryFile

import numpy as np


def 					_UpperCAmelCase				(						a__  ,	a__  ,	a__):

			'''simple docstring'''



			a_						:						List[Any] 							= 0
			if start < end:
						a_						:						Dict 							= randint(a__  ,	a__)
						a_						:						List[str] 							= a[end]
						a_						:						Tuple 							= a[pivot]
						a_						:						Tuple 							= temp

						a_							,					a_						:						List[Any] 							= _in_place_partition(a__  ,	a__  ,	a__)
						count += _in_place_quick_sort(a__  ,	a__  ,	p - 1)
						count += _in_place_quick_sort(a__  ,	p + 1  ,	a__)
			return count


def 					_UpperCAmelCase				(						a__  ,	a__  ,	a__):

			'''simple docstring'''



			a_						:						Optional[int] 							= 0
			a_						:						Union[str, Any] 							= randint(a__  ,	a__)
			a_						:						Union[str, Any] 							= a[end]
			a_						:						Any 							= a[pivot]
			a_						:						Any 							= temp
			a_						:						int 							= start - 1
			for index in range(a__  ,	a__):
						count += 1
						if a[index] < a[end]:  # check if current val is less than pivot value
									a_						:						str 							= new_pivot_index + 1
									a_						:						Optional[Any] 							= a[new_pivot_index]
									a_						:						str 							= a[index]
									a_						:						Union[str, Any] 							= temp

			a_						:						Union[str, Any] 							= a[new_pivot_index + 1]
			a_						:						Tuple 							= a[end]
			a_						:						Any 							= temp
			return new_pivot_index + 1, count


__snake_case				:      Union[str, Any]   		=			TemporaryFile()
__snake_case				:      Dict   		=			1_00  # 1000 elements are to be sorted


__snake_case		, __snake_case				:      int   		=			0, 1  # mean and standard deviation
__snake_case				:      Tuple   		=			np.random.normal(mu, sigma, p)
np.save(outfile, X)
print("""The array is""")
print(X)


outfile.seek(0)  # using the same array
__snake_case				:      str   		=			np.load(outfile)
__snake_case				:      Dict   		=			len(M) - 1
__snake_case				:      Dict   		=			_in_place_quick_sort(M, 0, r)

print(
    """No of Comparisons for 100 elements selected from a standard normal distribution"""
    """is :"""
)



print(z)


